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This paper describes the probabilistic wind power forecasting method that was used to win the wind track of the Global Energy Forecasting Competition 2014 (GEFCom2014). Executing a consistent machine learning framework for fitting independent models for each wind zone and quantile allowed us to automate our process for the duration of the competition. We used gradient boosted machines (GBM) for multiple...
This paper outlines a numerical recipe used to solve the ICDM 2015 competition to associate devices and cookies. The presented model utilizes binomial classification at three stages. The first stage imposed a shared IP address constraint to produce an initial set of candidate matches. The second stage utilized gradient boosted machines with 90 calculated features. This stage was the focal point for...
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